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@kururu-abdo
Created July 23, 2023 12:45
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//drop columns
df.drop(['Unnamed: 0.1', 'Unnamed: 0'], axis=1, inplace=True)
//count sample or get dimensions
x_train_pr1.shape
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df.corr()['price'].sort_values() // most feature corellated with price

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